Windows Credentials in Registry Reg Query
Description
The following analytic identifies a process command line related to the discovery of possible password or credentials in the registry. This technique is being abused by adversaries or post exploitation tools like winpeas to steal credentials in the registry in the targeted host. Registry can contain several sensitive information like username and credentials that can be used for privilege escalation, persistence or even in lateral movement. This Anomaly detection can be a good pivot to detect a suspicious process querying a registry related to password or private keys.
- Type: Anomaly
- Product: Splunk Enterprise, Splunk Enterprise Security, Splunk Cloud
- Datamodel: Endpoint
- Last Updated: 2022-11-30
- Author: Teoderick Contreras, Splunk
- ID: a8b3124e-2278-4b73-ae9c-585117079fb2
Annotations
ATT&CK
Kill Chain Phase
- Exploitation
NIST
- DE.AE
CIS20
- CIS 10
CVE
Search
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| tstats `security_content_summariesonly` count min(_time) as firstTime max(_time) as lastTime from datamodel=Endpoint.Processes where `process_reg` AND Processes.process = "* query *" AND Processes.process IN ("*\\Software\\ORL\\WinVNC3\\Password*", "*\\SOFTWARE\\RealVNC\\WinVNC4 /v password*", "*\\CurrentControlSet\\Services\\SNMP*", "*\\Software\\TightVNC\\Server*", "*\\Software\\SimonTatham\\PuTTY\\Sessions*", "*\\Software\\OpenSSH\\Agent\\Keys*", "*password*") by Processes.process_name Processes.original_file_name Processes.process Processes.process_id Processes.process_guid Processes.parent_process_name Processes.parent_process Processes.parent_process_guid Processes.dest Processes.user
| `drop_dm_object_name(Processes)`
| `security_content_ctime(firstTime)`
| `security_content_ctime(lastTime)`
| `windows_credentials_in_registry_reg_query_filter`
Macros
The SPL above uses the following Macros:
windows_credentials_in_registry_reg_query_filter is a empty macro by default. It allows the user to filter out any results (false positives) without editing the SPL.
Required fields
List of fields required to use this analytic.
- _time
- Processes.dest
- Processes.user
- Processes.parent_process_name
- Processes.parent_process
- Processes.original_file_name
- Processes.process_name
- Processes.process
- Processes.process_id
- Processes.parent_process_path
- Processes.process_path
- Processes.parent_process_id
- Processes.parent_process_guid
- Processes.process_guid
How To Implement
To successfully implement this search, you need to be ingesting logs with the process name, parent process, and command-line executions from your endpoints. If you are using Sysmon, you must have at least version 6.0.4 of the Sysmon TA. Tune and filter known instances of wermgr.exe may be used.
Known False Positives
unknown
Associated Analytic Story
RBA
Risk Score | Impact | Confidence | Message |
---|---|---|---|
25.0 | 50 | 50 | reg query commandline $process$ in $dest$ |
The Risk Score is calculated by the following formula: Risk Score = (Impact * Confidence/100). Initial Confidence and Impact is set by the analytic author.
Reference
- https://attack.mitre.org/techniques/T1552/002/
- https://github.com/carlospolop/PEASS-ng/tree/master/winPEAS
- https://www.microsoft.com/en-us/security/blog/2022/10/14/new-prestige-ransomware-impacts-organizations-in-ukraine-and-poland/
Test Dataset
Replay any dataset to Splunk Enterprise by using our replay.py
tool or the UI.
Alternatively you can replay a dataset into a Splunk Attack Range
source | version: 1